E-Discovery Analytics Advisor Overview • The E-Discovery Analytics Advisor guides case teams in leveraging e-discovery technology throughout the lifecycle, emphasizing generative AI tools. • Provide expertise on RelativityOne aiR suite applications for document review, privilege analysis, and case strategy development. • Draft and refine AI criteria and prompts, ensuring validation and defensibility in workflows. • Develop protocols for AI-assisted document review, privilege review, and production quality control. • Design defensibility measures for AI workflows, including sampling plans and precision metrics. • Support pre-production workflows, including privilege identification and redaction quality control. • Train attorneys on e-discovery technology, focusing on generative AI tools and practical applications. • Stay updated on generative AI developments in e-discovery and translate insights into practice. E-Discovery Analytics Advisor Key Responsibilities & Duties • Consult with case teams on effective e-discovery technology application to achieve case goals. • Advise teams on RelativityOne aiR suite use cases, scoping, and expected outcomes. • Draft and test AI criteria for relevance, privilege, and custom analyses. • Implement protocols for AI-assisted workflows and quality control measures. • Design defensibility measures for AI workflows, ensuring compliance with legal standards. • Support pre-production workflows, including privilege log generation and redaction quality control. • Provide user management support for e-discovery applications like RelativityOne and Opus 2. • Train attorneys and colleagues on generative AI tools and their practical applications. • Monitor industry developments and adapt practices to align with evolving standards. E-Discovery Analytics Advisor Job Requirements • Bachelor's degree required, preferably in a related field. • Relativity certifications preferred; hands-on experience with Relativity aiR strongly desired. • Minimum of three years of e-discovery experience, advising on technology applications. • Proven experience applying generative AI to document review and privilege workflows. • Knowledge of advanced e-discovery tools like predictive coding and data analytics. • Understanding of prompt engineering principles and validation concepts. • Familiarity with statistical validation methods for review quality control. • Awareness of ethical considerations in AI use for legal work. • Ability to manage multiple projects and priorities effectively.